Director of Data

Rugiet Health•Austin, TX

23h•Remote

About The Position

The Director of Data & Analytics will lead Rugiet’s data ecosystem, including infrastructure, analytics, attribution, forecasting, and personalization. The role combines strategic leadership with hands-on analytical work and includes leading a small team as the company migrates its data warehouse to Snowflake and develops a scalable, ML-ready foundation. Reporting directly to the CGO, the Director will partner with Marketing, Product, Engineering, Operations, and Finance. The position is responsible for setting data strategy, developing two analysts/data engineers, improving how data work is prioritized, enabling BI self-service, and establishing reliable, governed data assets and processes. The Director will lead Snowflake migration and ETL/BI improvements, partner with Product and Engineering on data for personalization and machine-learning experiences, and build growth and retention analytics. This includes LTV models, attribution reporting, retention dashboards, churn analysis, experimentation, marketing mix modeling, and forecasting in partnership with Finance. Rugiet is a remote-first company.

Requirements

At least 7 years of experience in Data & Analytics.
At least 2 years of experience leading teams.
Hands-on experience with modern data stacks, including Snowflake or an equivalent data warehouse.
Experience with ETL and pipeline tools such as Segment, Fivetran, dbt, or similar.
Experience with BI tools such as Domo, Looker, or Mode.
Experience with analytics tools such as GA4, Segment, or Mixpanel.
Experience with attribution tools or methods, including Northbeam, multi-touch attribution structures, or familiarity with marketing mix modeling.
Advanced SQL skills and strong data-modeling discipline.
Ability to turn messy data into clear insights and communicate them to executives.
Experience enabling BI self-service and building stakeholder capability.
Strong understanding of data governance and privacy/security practices.

Nice To Haves

High-growth direct-to-consumer or telehealth experience is strongly preferred.
Domo experience is strongly preferred.
Python or R experience for LTV modeling, churn prediction, marketing mix modeling, forecasting, and ML feature engineering.
Experience with Blotout, Growthbook, or similar tools.
Background in healthcare, wellness, or subscription businesses.
Experience building or supporting personalization or ML systems in partnership with Product.

Responsibilities

Define Rugiet’s data strategy and lead its execution across infrastructure, analytics, and modeling.
Manage and develop two analysts/data engineers, strengthening analytical rigor, ownership, and output.
Create a transparent intake and prioritization system for data requests and set standards that focus the team on analysis rather than data mining.
Promote BI self-service by training teams and building intuitive, reliable dashboards.
Lead the migration to Snowflake and design a scalable data warehouse.
Optimize ETL pipelines, including Segment-to-Snowflake-to-BI workflows, to support near-real-time reporting where needed.
Replace one-off dashboards and inconsistent models with reusable, governed, version-controlled data assets.
Establish data governance standards for schemas, taxonomies, and naming conventions.
Assess the long-term scalability of BI tooling and develop stronger self-service offerings for organizational decision-making.
Partner with Product and Engineering to develop data inputs, segmentation logic, and feature sets for personalization and ML-driven experiences.
Structure behavioral and lifecycle data for algorithmic use to improve retention, engagement, and patient outcomes.
Ensure data pipelines and infrastructure support scalable ML model training, monitoring, and continuous optimization.
Build LTV models and curves segmented by acquisition channel, offer, audience, and treatment category.
Develop daily multi-touch attribution reporting and bring core attribution capabilities in-house.
Build retention OKRs and dashboards with clear, intuitive views for the business.
Attribute cancellations and churn to lifecycle, email, and SMS campaigns using statistical rigor.
Design and analyze A/B tests across the site, funnel, CRM, and product experience.
Develop marketing mix modeling in Python to inform budget allocation.
Partner with Finance on forecasting models for demand, inventory, and revenue planning.